In 1997, years before anyone made a profession of worrying about a runaway Snowflake bill, Keith Alsheimer filed a patent about cleaning floors. The document described a building-block training system for facility cleaners: pictorial instructions arranged in sequence, showing what to do, what not to miss, and what to avoid. It was practical, visual, and almost stubbornly clear. The patent was granted the following year. Read now, it feels less like an outlier on his résumé than its secret table of contents.
Alsheimer's work has repeatedly landed where complicated systems meet busy people. The system might be a military unit, a janitorial supply chain, an open-source database, an observability platform, or a sprawling cloud data estate. The people still need the same thing: a useful picture of reality and a credible next move.
That is a less glamorous description of marketing than the usual one, which may be why it is more convincing. As chief marketing officer at Unravel Data, Alsheimer works in a market with enough nouns to fog a conference hall: DataOps, FinOps, observability, actionability, agentic AI. His public case strips the pile back to two jobs. Find the inefficiency. Fix the inefficiency. Most software is quite pleased with itself after job one.
“Identifying inefficiencies is problem one, and fixing it is problem two.”Keith Alsheimer, 2025
First, the team. Then, the task.
The earliest public chapter is the Army. In 1984, Alsheimer appeared in the Congressional Record among ROTC cadets appointed as second lieutenants in the Regular Army. He served for eight years and rose to captain. He has not treated that period as decorative biography. In a 2020 essay, he reached back to Army Rangers to write about high-performing teams, trust, shared standards, and the way people behave when pressure removes the option of pretending.
Former colleagues describe the civilian version of those habits. One calls him a leader who brings voices into the room, aligns stakeholders, and mixes evidence with instinct. Another points to emotional intelligence and an ability to get the facts onto the table. There is even the obligatory Massachusetts footnote: a colleague jokes that Alsheimer's Boston Bruins loyalty is his one conspicuous defect.
Leadership, in this telling, is not stagecraft. It is the architecture around performance. People need to know the objective, the intermediate milestones, and where they have room to act. Alsheimer's language tends to pair autonomy with accountability. Trust the person, clarify the standard, and avoid confusing a crowded dashboard with a plan.
A founder learns where slogans go to die
After the Army and a stint in the commercial cleaning industry, Alsheimer moved from operating inside a supply chain to rebuilding it. He founded eSpendwise in 2000 and led it as chief executive until the business was sold in 2012. The company grew from Cleanwise, an online procurement system designed for the janitorial and sanitation market. It offered large, multi-location businesses a way to purchase supplies, reach training material, and manage information through one system.
This is wonderfully unabstract founder training. Cleaning supplies must arrive. A distributor must participate. A customer must understand the process. Reports must reconcile with purchases. Nobody has time to admire the category narrative while a facility waits for stock. The work either moves or does not.
The experience also made Alsheimer a buyer of the sort of enterprise technology he would later market. As eSpendwise CEO, he spoke publicly about the operational role of Postgres management. Later he joined EnterpriseDB as CMO, selling a commercial path into that same open-source database world. He had crossed the table.
Founder experience leaves a particular kind of scar tissue. It makes cost tangible. It makes alignment less like a workshop exercise and more like survival. At EnterpriseDB, Alsheimer pushed account-based marketing as a coordinated program rather than a campaign wearing a more expensive name. Sales and marketing needed the same target accounts, the same plays, and an agreed route from attention to revenue.
In 2017 he presented that approach during a run in which EnterpriseDB had recorded 30 consecutive quarters of subscription revenue growth. His remit covered sales development, communications, product marketing, and brand. The scope says something about his style: the story was not meant to sit in a corner. It had to travel through the commercial system.
The translator changes dictionaries
From EnterpriseDB, Alsheimer became CMO at Logz.io in 2019. The nouns changed from databases to machine data, open-source ELK, monitoring, troubleshooting, and security. He later served as vice president of global marketing at performance-testing company Neotys. Then came Unravel Data, where he was publicly speaking as head of marketing by 2022 and now serves as chief marketing officer.
There is a clean progression across those companies. A database must perform. Applications must be observed. Tests must reveal strain before users do. Data platforms must remain reliable without turning their operators into full-time detectives. Each category adds instrumentation, and each risks adding a new console that explains why the other consoles are unhappy.
Alsheimer's role is to make that accumulation intelligible to people who enter from different doors. Engineers care about failed jobs and slow queries. Finance leaders care about a cloud bill that has acquired weather. Executives care about the business value promised when the platform was approved. A good story cannot flatten those concerns into one generic buyer. It must show how they touch.
“Every company is a data company.”Keith Alsheimer, Data Summit 2022
At Data Summit in Boston in 2022, Alsheimer and colleague Chris Santiago described data teams caught between demand, complexity, skills shortages, and limited visibility. The session argued that web application monitoring tools leave gaps when applied to modern data stacks. Seeing the pieces is not the same as understanding the system.
That distinction has only become more expensive. In a 2025 interview about a free Snowflake analyzer, Alsheimer cited estimates that 30 to 40 percent of data-platform and underlying cloud spend may be waste. Granularity is the villain. Thousands of people create queries, configurations, jobs, and consumption choices. The bill arrives as a number; the cause lives in a thicket.
The cloud bill's invisible slice
Software should finish the sentence
The fashionable answer to every enterprise problem is now an AI agent. Alsheimer's version is more demanding than adding a chat box and an adjective. In his current framing, observability reports the condition, while actionability guides or performs the repair. His neatest summary is also his sharpest: “Visibility without action is just expensive watching.”
The appeal is obvious. A slow query does not become less slow because its diagnosis has excellent typography. A cost anomaly is not savings. A recommendation waiting in a queue may be accurate, elegant, and entirely inert. Unravel's present story is that autonomous agents can close that last distance across Databricks, Snowflake, and BigQuery, handling work in FinOps, DataOps, and data engineering while retaining controls.
For Alsheimer, this is a technology argument built on a human observation: expertise is scarce, and repetitive troubleshooting is a poor use of it. In 1998, his patent encoded expert cleaning practice into pictures and sequences that could travel. In 2026, the promise is to encode optimization knowledge into agents that can investigate and act. The machinery is different. The managerial question is almost identical.
That continuity is what makes his career more interesting than its titles. Army captain, inventor, founder, CEO, CMO: each role can be presented as a separate badge. Seen together, they look more like revisions of one working draft. How do you make the objective legible? How do you equip a team to move without waiting for a hero? How do you turn information into behavior?
His published writing offers small clues about how he answers. He likes questions, concrete comparisons, and frameworks that force a decision. A Postgres essay once borrowed Beyoncé and the Golden Arches to make technical distinctions memorable. His go-to-market articles begin with the choices a team must make, not a grand theory of marketing. Even his praise for colleagues dwells on their ability to translate technical value into human terms. The humor helps, but it also performs a useful commercial function. When the subject is dense, a familiar image gives everyone a place to stand. Clarity need not be solemn to be serious.
Enterprise software will never run out of complexity. It is too profitable, too necessary, and too fond of naming things. Alsheimer has built his career on the countervailing trade: preserve the sophistication, remove the fog, and make the next step hard to misunderstand. The cleaning-floor patent was not a detour. It was the prototype.